帮朋友问一下……哪些工作不会被AI取代？

这里是NPR的《金钱星球》。

This is Planet Money from NPR.

去年夏天，查理·贝克非常无聊。他是一名即将升入大四的学生，在新泽西州社区事务部实习。在令人兴奋的日子里，他做的就是往电子表格里录入数据。

Last summer, Charlie Baker was very bored. He was a rising college senior, had an internship at the New Jersey Department of Community Affairs. Entering data into spreadsheets, that was what he did on an exciting day.

有一天，他在休息室里。

And one day, he's in the break room.

我脑海里浮现的是米黄色，一切都是米黄色的。

I'm picturing beige, everything beige.

或者是灰色。而且它还有一种类似二手店的味道，如果这能让你明白的话。

Or gray. It's like and it also it has this sort of smell of, like, a thrift store, if that if that makes sense.

嗯。是的。我确实知道那种味道。我不是，你知道，我并不为你喜欢它而感到高兴，但我知道那种味道。

Mhmm. Yep. I do know that smell. It's not I, you know, I don't love it for you, but I know it.

在那个气味刺鼻的休息室里，他在桌子上看到了一些在其他情况下并不会让人兴奋的东西。

And in that pungent break room, he sees on the table something that in other circumstances would not be exciting.

有人把一本LSAT备考书落在那里，我当时就想，哦，也许我该看看这个。

Someone had left out, like, a LSAT studying book, and I was like, oh, maybe I should check this out.

他开始钻研这本书，为了好玩而做法学院入学考试的练习题。这简直是完美的法学院浪漫邂逅。LSAT备考书和查理在休息室相遇，剩下的就是历史了。

He starts working through this book, doing practice questions for the law school admissions exam for fun. And it is like the perfect law school meet cute. LSAT book and Charlie run into each other in the break room, and the rest is history.

全是些奇怪的小谜题。就像是有史以来最复杂的谜语。我当时就想，哦，我真的应该做这个。

It's all weird little, like, puzzles. The most convoluted riddles, like, anyone has ever written. And I was like, oh, I should really do this.

做这个指的是参加LSAT考试并去法学院。

Do this meaning take the LSAT and go to law school.

但几乎立刻，查理脑海中的背景音乐就变了。

But almost immediately, it's like the soundtrack shifts in Charlie's mind.

也许他并不是在一部有趣的法学院浪漫喜剧里。也许他和所有他认识的人实际上生活在某种反乌托邦科技恐怖片中，有一个邪恶的机器人在四处游荡，夺走每一个工作岗位。

Maybe he's not in a fun law school rom com. Maybe he and everyone he knows is actually living in some kind of dystopian technological horror movie, where there's an evil robot on the prowl going after every last job.

我不知道。如果最终可能被AI聊天机器人取代，我不确定现在投入三年时间去法学院是否值得。

I don't know. I don't know if if it's worth the investment now to go to law school for three years if I'm potentially going to just be replaced by an AI chatbot.

人工智能。很多人对此感到担忧。

AI. A lot of people are worried about this.

我完全不知道该如何规划未来。

I have no idea how to plan for the future.

这太不确定且令人恐惧。有什么是人工智能不会自动化的呢？

It's so uncertain and scary. What would AI not automate out?

安娜·阮，就像查理一样，担心机器人。她三十多岁，在科技行业从事产品设计已有十年。

Anna Nguyen, like Charlie, is worried about the robots. Anna is in her thirties. She's been doing product design in tech for ten years.

你喜欢你的工作吗？

Do you like your job?

是的，我喜欢。工作很棒。但你也知道，整个行业都在发生迫在眉睫的裁员。

Yeah. I I do. It's great. But then there's also, you know, all the looming layoffs that are happening across the industry.

她怀疑其中一些裁员已经是由人工智能驱动的，并担心自己可能是下一个。已经有软件能让像她这样的设计师效率大大提高。她认为人工智能最终有可能完全取代她的位置。

She suspects that some of these layoffs are already driven by AI, and she's worried that she could be next. There's already software that can make designers like her a lot faster. She thinks it's possible that AI could eventually cut her out of the loop entirely.

于是安娜开始在脑海中翻阅各种工作，试图想象哪些工作能在人工智能时代存活下来。

So Anna has started paging through a list of jobs in her mind, trying to imagine which of them might survive AI.

现在什么都说不准

And it's anything right now

体力活，比如水管工。我的意思是，要自动化这种工作还得等上好一阵子。我接下来考虑的是电工。

physical, maybe a plumber. I mean, it's it's gonna take a while before you could automate that. I was thinking maybe electrician next to look at.

或者她妈妈的工作，美甲师。

Or there's her mom's job, nail tech.

她总是说，你知道的，你可以回这里来。这里有很多活儿。比如，你要是愿意，我都准备好和你一起创业了。

She's always like, you know, you can come back here. There's there's a lot of work. Like, I'm ready to start a business with you if you want.

不过也说不好，也许电焊工也行。

But also, who knows? Maybe welding.

我我看过一个视频，里面有人接受过培训。我当时就想，

I I saw, like, a video with someone who trained for it. I was like,

她目前还处于调研阶段，但她非常认真对待这件事，正在深入实质性问题。

She's still in the research phase, but she's taking it really seriously, getting down to brass tacks.

学校要花多少钱，我第一年、第二年当学徒可能能赚多少。所以真的是在做出重大决定前先好好算算账。

What the school cost, how much maybe I would be making the first year, second year as an apprentice. So really kind of, you know, doing the numbers before making a leap.

查理也在算这笔账。读法学院到底值不值得？

Charlie is doing the numbers too. Is law school going to be worth it?

如果我毕业时背负着，比如说，10万美元的债务，进入一个就业岗位正在减少的法律领域，那处境就真的很糟糕了。

If I'm gonna graduate with, say, whatever, a $100,000 in debt to a legal field where they're decreasing the jobs, I mean, that's a really bad situation.

所以尽管他对LSAT考试情有独钟，他还是决定暂时推迟读法学院。先观望一下。安娜也处于类似的等待状态，他们俩都在为人工智能的未来做准备。

So despite his love affair with the LSAT, he has decided to delay law school for now. Wait and see. Anna is also in a sort of holding pattern, Both of them just bracing for the AI future.

查理和安娜绝对不是个例。我的意思是，我也在担心这个问题，我很多朋友也是。担心应该选择或避开哪些职业，担心自己的孩子应该朝哪个方向发展或不发展。

Charlie and Anna are so, so not alone. I mean, I am worried about this, and so are lots of my friends. Worried about which jobs they should steer towards or away from. Worried about what direction their kids should go or not go.

我们数十位听众都就此给我们来信，说诸如：也许我现在做瑜伽老师的副业反而是最稳妥的选择；我父母是做房地产的，我从没想过会这么说，但也许那才是我应该做的。

Dozens of you, our listeners, have written into us about this, saying things like, maybe my yoga teacher side gig is actually my safest bet now. And my parents were in real estate, and I never thought I'd say it, but maybe that's what I should do.

我感觉我们所有人都不知道该如何思考这个问题。比如，即使你能很快记住所有现有的工作，其中哪些可能是你的避风港？你该如何判断呢？

It feels to me like we all have no idea how to think about this. Like, even if you can really quickly remember all the jobs that exist, which of them might be your safe harbor? How do you figure that out?

你好，欢迎来到《金钱星球》。我是阿曼达·奥龙奇克。我是莎莉·赫尔姆。

Hello, and welcome to Planet Money. I'm Amanda Oronczyk. And I'm Sally Helm.

帮朋友问一下，哪些工作能免受AI影响？

Asking for a friend, which jobs are safe from AI?

今天的节目中，我们将与两位研究人员对话，他们为像查理、安娜、我和莎莉这样的人勾勒出了未来的初步蓝图——一些可能的规划方案。他们提出了两种思考框架，探讨AI将如何影响就业：哪些工作可能会消失，哪些更可能保留，以及哪些会以我们尚未想象的方式发生变化。

Today on the show, we talk to two researchers who have come up with some first drafts of the future, some potential blueprints for people like Charlie and Anna And me. And Sally. Two frameworks for thinking about how AI will affect jobs, which might disappear, might be more likely to stay, and which will change in ways we haven't even imagined.

我很喜欢这些对话，既能了解更多关于机器的知识，也能更深入理解身为人类的意义。在开始报道这个故事时，我其实怀着一个秘密使命，一个连我自己都没有完全明确的目标。说实话，我真正想找到的是一份能完全免疫AI的工作清单——那些超级智能的思维机器无法胜任的工作。有一瞬间，我以为我找到了。

I love these conversations knowing more about the machines, but also about what it actually means to be human. I had kind of a secret mission as I set out to report this story, one that I hadn't even fully articulated to myself. What I really wanted to find, if I'm being honest, is a list of jobs that are just gonna be immune to AI. The super intelligent thinking machines will not be able to do them. And for a moment, I thought I'd found it.

我现在面前就打开了这份清单。它涵盖了近千种职业，并按所谓的“AI暴露度”进行了排名。在我完全理解这个术语的含义之前，我简直觉得中大奖了。这份清单会告诉我和安娜、查理所有我们需要了解的关于AI未来的信息。

I have the list pulled up in front of me right now. It takes almost a thousand jobs and ranks them by something called AI exposure. And before I understood precisely what that means, I was like jackpot. This list is gonna tell me and Anna and Charlie everything we need to know about our AI future.

清单上列出了各种工作：助产士、侦探、农药处理员、喷洒员和施药员（植被类）。

On the list are all kinds of jobs, midwives, detectives, pesticide handlers, sprayers, and applicators, comma, vegetation.

哦，那里有很多很酷的职业。挖泥船操作员，这个就挺酷的。

Oh, there's lots of cool ones there. Dredge operator, that one's pretty cool.

这是丹尼尔·洛克。他是这份名单的幕后推手。他这篇论文的合著者是OpenAI的研究人员。他们实际上在这项研究中使用了人工智能作为工具。

This is Daniel Rock. He is the man behind the list. His coauthors on his paper about this were researchers at OpenAI. They actually used AI as a tool in this study.

他们所做的是，他们选取了这大约一千种职业，并将每种职业视为一系列任务的集合。

And what they did is they took these thousand or so jobs and looked at each job as a bundle of tasks.

是的。比如如果你是助产士、侦探或农药处理员会做的事情。

Yeah. Things you do if you are a midwife or a detective or a pesticide handler.

人们在经济活动中所做的两万个任务。

20,000 tasks that people do in the economy.

这些任务列表的来源是一个名为ONet的惊人政府数据库。如果你去查看它——我建议你去看看——我还建议你设个计时器，否则你可能会像我一样，看了大概半小时后抬起头，才意识到自己刚刚读完了咖啡师的全部任务清单。丹尼尔和我一起看了他作为经济学家的任务清单。根据这个，你有16项任务。对吗？

The source of these task lists is an amazing government database called ONet. If you go look at it, which I recommend you do, I also recommend that you set a timer, or you may find yourself, as I did, looking up after, like, half an hour and realizing that you have just read the entire task list for baristas. Daniel and I looked at the task list for him, an economist. According to this, you have 16 tasks. Is that right?

是的。我上次数过。是的。听起来完全正确。

Yeah. Last I counted. Yeah. That's it sounds about exactly right.

好的。向公众解释政策的经济影响，监督研究项目，以及学生的研究项目。你做过这些吗？

Okay. Explain economic impact of policies to the public, supervise research projects, and students study projects. Have you ever done that?

听起来是的。我昨天就在做这些。

That sounds yeah. I was doing that yesterday.

丹尼尔的论文研究了O*NET中列出的19,265项任务。该论文对这些任务进行了评估，衡量了每项任务受AI影响的程度。丹尼尔测量的是暴露度，基本上是指这些大型语言模型能在多大程度上帮助我们完成任务。如果AI能帮助人类在至少一半的时间内完成任务，丹尼尔就将其标记为e1。如果AI完全无法提供帮助，则为e0。

Daniel's paper looked at 19,265 tasks listed in O*NET. The paper took those tasks and evaluated how exposed each one is to AI. Daniel's measuring exposure, which means basically how much these large language models can help us do our tasks. If the AI can help a human complete a task in at least half the time, Daniel labels it e one. If AI can't really help at all, it's e zero.

然后是e2，这是一种介于中间的分数。

Then there's e two, which is a sort of in between score.

e2的意思是，是的，你可以获得一些好处，但你必须围绕它构建系统。

E two is, yeah, you could get some benefits, but you have to build systems around it.

就像，AI不能直接开箱即用地做这件事。它需要一些额外的软件或附加的东西来提供帮助。所以我们调出了一名急症护理护士的任务清单。他们有26项任务。比如说，进行血液和血液制品输血。

Like, AI can't just do this one out of the box. It'd need some extra software or something tacked on in order to help. So we pulled up the task list for an acute care nurse. They have 26 tasks. Let's say, administer blood and blood product transfusions.

没错。所以，在AI系统做这件事的可怕未来噩梦世界里，可能不是大型语言模型或这类现有技术在操作。因此，我们将其称为e0。

Right. So in the horrifying future world nightmare where AI systems do this, it's probably not a large language model or like this vintage of technology is doing that. So we're gonna call that an e zero.

所以没有暴露？

So not exposed?

没有暴露。

Not exposed.

所以你逐个任务进行。

So you go task by task.

是的。所以这里我有与患者护理相关的文档数据。

So yeah. So here I have document data related to patient's care.

是的。这看起来像是大型语言模型可以帮忙的事情。所以，是的，那就像是一个任务。

Yeah. That seems like something a large language model could help. So, yeah, that would be like an e one task.

然后你给整个工作一个暴露评分。瞧，暴露清单就出来了。

And then you give an exposure score to the job as a whole. And voila, the exposure list.

当我第一次打开它时，我脑海里仿佛响起了鼓声。因为这是一种具体的方式来看待这个关于未来的大问题，关于人工智能将如何开始深入劳动力市场并搅动一切。我正在看这份清单。嗯。我已经把它排序好了。

When I first opened it, there was like a drum roll in my mind. Because it is a concrete way to look at this big question about the future, about how AI is gonna start reaching into the labor market and shaking things up. I'm looking at this list. Mhmm. I've put it in order.

在最底层，我们有井口泵操作员。是的。我们最爱的挖泥船操作员。

Down at the bottom, we've got wellhead pumpers. Yeah. Our favorite dredge operators.

喜欢挖泥船操作员。

Love the dredge operator.

浇注工和铸造工，逗号，金属。

Pours and casters, comma, metal.

同样在低端，受AI影响较小的职业有运动员、舞者、快餐厨师，以及如Adewyn所料，大量体力蓝领工作。与此同时，在顶端，有很多知识工作者、翻译、作家。

Also on the low end, less exposed to AI, there were athletes, dancers, short order cooks, and as Adewyn suspected, a lot of physical blue collar jobs. Meanwhile, at the top, a lot of knowledge workers, translators, writers.

我们有公共关系专家。为什么他们排名这么高？

We have public relations specialists. Why are they so high?

哦，哇。是的。这个我亲眼见过。当一位公共关系专家第一次使用GPT-4时，我看到了她恍然大悟的样子。她，你知道，让它以她的语气为她写了一篇新闻稿，她说完成得绝对出色。当然其中也夹杂着一点恐惧，因为她说，哇，这就像我职业生涯的头几年，只是现在在一台机器里。

Oh, wow. Yeah. So I've I've seen this one in person. When a public relations specialist used GPT-four for the first time and I saw the light bulb go off, She, you know, had it write a press release for her in her tone, and she said it did an absolutely great job. Now there was a little bit of fear in there too, because she said, wow, this is like the first few years of my career, like, just in a machine.

是的。所以这就是丹尼尔的名单让人感到害怕的地方。这个想法是，这台机器已经读遍了我们所做的一切，现在也许它不再需要我们了。

Yeah. So this is the thing that feels scary about Daniel's list. The idea that this machine has read up on everything we've ever done, and now maybe it doesn't need us.

感觉排在列表顶端的这些工作

It feels like the jobs at the top of

似乎即将消失，被AI取代。我的意思是，这基本上不就是一份自动化清除名单吗？

this list are going to disappear, killed by AI. I mean, like, is this basically an automation hit list?

不。这绝对不是一份自动化清除名单。而是一份评估这些工作变革潜力的清单。

No. It's absolutely not an automation hit list. It's instead a what is the potential for this work to change list?

必须承认这种说法不够吸引人。但这确实是丹尼尔想向我强调的重点。接触AI并不等同于这个工作会被自动化取代。所以安娜、查理

That is admittedly not as catchy a way to describe it. But that is really the big point that Daniel wanted to stress to me. Exposure to AI is not the same thing as this job will be automated. So Anna, Charlie

还有你，莎莉。

And you, Sally.

我们看到的不是安全与不安全工作的清单。丹尼尔·洛克在这篇论文中提出的核心问题并不是：我能否列出一份免受AI影响的工作清单，让莎莉·赫尔姆晚上睡得更安稳？他对AI整体有一个更宏大的问题。他想弄清楚：我们正在讨论的变革影响范围有多大？AI是那种会渗透到经济几乎每个角落的技术吗？

We are not looking at a list of safe and unsafe jobs. The main question that Daniel Rock is asking in this paper is not, can I come up with a list of jobs that are safe from AI so that Sally Helm can sleep easier at night? Daniel has a much bigger question about AI as a whole. He wants to figure out, how far reaching is the change we're talking about here? Is AI the kind of technology that will seep into basically every corner of the economy?

经济学家称之为通用目的技术。那么它到底是这样的技术，还是作用范围更有限？

Economists call that a general purpose technology. So is it that, or is it something more limited?

这更像是电力，还是像Instagram？它们的影响非常不同，对吧。Instagram显然是一种通用技术，电力也还行。嗯，它挺好的。

Is this like electricity, or is it, you know, like Instagram? They're very different, right, in terms of the the implications. Right. Instagram is obviously a general purpose technology, electricity was okay. Like, it's fine.

没错。Instagram彻底改变了。

Right. Instagram changed at all.

开个玩笑。显然，电力才是通用技术。它极大地改变了生活和工作，如今几乎没有工作不与电力相关。至少在我看来是这样。当你查看这些暴露分数时，这一点非常清楚。

Just kidding. Obviously, electricity is the general purpose technology. It changes life and work so much that almost no job today doesn't have something to do with electricity. At least, it feels that way to me. And when you look at these exposure scores, it's really clear.

AI将触及许多行业。丹尼尔

AI is gonna touch a lot of sectors. Daniel

和

and

他的合著者发现，是的，看起来像是一种通用技术。这对我们意味着什么，我同时感到有些泄气又有点希望。丹尼尔告诉我，由于AI似乎是这种重大的新型通用技术，对经济的改变将如此巨大，以至于我们很难从现在的位置去想象。就像，在电力出现之前，没有电工、电气工程师或灯光技师这些职业，而如今它们都列在O*NET中。

his coauthors find, yeah, seems like a general purpose technology. And what that means for us is something that I found simultaneously sort of deflating and kind of hopeful. Daniel told me that because AI appears to be this big new general purpose technology, the changes to the economy will be so vast that they are very hard to imagine from where we stand now. Like, you know, before electricity, there was no job electrician or electrical engineer or lighting technician, all of which are today listed in O*NET.

太多事情将会改变，我们真的无法说哪些工作会消失，哪些工作会变得更重要。我们有点在说，你知道，让我们冷静一下，别再做那些关于工作将消失的预测了。

So much is gonna change that we really can't say which jobs are going away, which jobs are gonna become more important. We're kind of saying, you know, let's let's cool it with all of the prognostication about how jobs are going away.

这令人沮丧，因为这意味着我没有非常具体的东西可以带回给查理和安娜。但这是丹尼尔论文的一个重要启示。如果你真的认真对待我们正在讨论的是类似电力级别的变革，就必须承认劳动力市场的变化可能不是你最初想象的那样。它们可能更大、更奇怪，可能更好或更糟。

And this is frustrating because it means I don't have something very concrete to bring back to Charlie and Anna. But this is one of the big takeaways from Daniel's paper. Like, if you take really seriously that we're talking about something on the order of electricity here, you have to admit that the changes to the labor market might not be what you first imagine. They might be bigger and weirder. They might be better or worse.

基本上，你无法围绕它们制定计划。但你可以做的是从这个列表中看出哪些工作可能变化最大，至少最初是这样。查理和安娜是对的。按照这个标准，律师将会看到很多变化，而焊工的变化会较少。

Basically, you cannot plan around them. But what you can do is see from this list which jobs are likely to change the most, like at least at first. And Charlie and Anna are right. By that measure, lawyers are gonna see a lot of changes, and welders will see fewer.

但在这个语境下，“变化”是一个价值中立的词。丹尼尔很坚持。我们不应该听到“这个工作会变化”就认为“这个工作会消失”。

But change in this case is a value neutral word. Daniel is adamant. We should not hear this job will change and think this job will go away.

如果你真的高度暴露（于AI影响下），这对你来说可能是件大好事。如果你能用AI让自己效率提高一千倍。假设你是一名AI研究员。对吧？他们就是高度暴露的。

If you're really exposed, it could be great for you. If you could use AI to make yourself a thousand times more productive. Let's say you're an AI researcher. Right? They're highly exposed.

如果你能利用这些工具成为一名非常高质量的AI研究员，你可能会做得非常好，公司会非常乐意以更高的工资雇佣你。

If you can use these tools to be a really high quality AI researcher, you might you might do really well, and companies are gonna be really excited to hire you at higher wages.

是的。如果工人的生产率提高了，而公司和消费者对他们生产的东西需求更大，那么每个人都是赢家。所以有可能这些高度暴露的领域会出现爆炸性增长，成为非常好的去处。经济学家会称之为需求有弹性。

Yeah. If workers get more productive and companies and consumers want more of what they are producing, then everyone wins. So it could be that some of these highly exposed fields see an explosion of growth, that they're a really good place to be. Economists would say that demand is elastic.

当然，如果工人的生产率提高了，但世界对他们生产的东西并没有更多需求，即需求缺乏弹性，那就会导致失业。比如，也许我们只需要一定数量的新闻文章或Logo。所以如果新闻写作者和平面设计师的效率大大提高，这些工作的岗位就会变少。

Of course, if workers get more productive and the world doesn't want even more of what they're producing, demand is inelastic, that leads to job loss. Like, maybe we only need so many news articles or logos. And so if news writers and graphic designers get way more productive, there are fewer of those jobs available.

比如，如果我是一家公司，我看了这份清单后想，好吧。看起来我雇佣的某些人在这份清单上的排名相当高。也许我应该考虑自动化这些工作岗位。这样想合理吗？

Like, if I'm a company and I look at this list and I think, okay. Well, it looks like various people that I employ are pretty high on this list. Maybe I should think about automating those jobs. Like, does that make sense?

他们可能会这么想，但根据我们的数据，他们不应该这样考虑。

They might think that way, but not they should not think of it that way from on the basis of our data.

丹尼尔认为组织需要进行实验。他给我举了一个研究的例子，一家公司向两组律师助理提供了人工智能工具。一组被告知，就用这些工具来提高生产力。另一组则被告知，用这些工具来处理你工作中讨厌的部分。

Daniel thinks that organizations will need to experiment. He gave me an example of a study where a company gave an AI tool to two groups of paralegals. One group was told, just use these tools to get more productive. And the other group was told, use these tools to do the parts of your job that you hate.

在被告知‘用这个工具摆脱你不喜欢的工作’的办公室，律师助理的角色发生了变化。他们真正蓬勃发展起来，开始承担一些甚至像是初级律师的工作。而在另一个办公室，工具的采用率有限，并没有产生太大影响。

The office where they said use this tool to get rid of the things you don't like doing, the paralegal role changed. They they really flourished. They started working on some work that even seemed like junior attorney work. In the other office, there was limited adoption. It it didn't really make as much of a dent.

所以丹尼尔的论文确实告诉我们人工智能可能会改变哪些工作。但它没有告诉我们哪些工作会存活，哪些会消失。

So what Daniel's paper does tell us is which jobs AI might change. What it doesn't tell us is which jobs will live and which will die.

但在我寻求答案的过程中，我确实找到了另一篇论文，它给了我一个全新的视角来看待所有这一切，使用的同样是那份包含19000多项任务的清单，这些任务涵盖了整个经济体系中工人们正在做的事情。休息之后我们再聊。伊莎贝拉·洛伊萨是麻省理工学院的研究员。几年前，当她开始听到朋友们谈论人工智能时，她有了一个富兰克林·德拉诺·罗斯福式的顿悟时刻。

But in my quest to answer that question, I did find another paper that gave me a whole new way of looking at all of this, using that same list of 19,000 plus tasks that workers are doing all across the economy. That's after the break. Isabella Loisa is a researcher at MIT. When she started to hear her friends talk about AI a couple of years ago, she had a Franklin Delano Roosevelt moment.

我从不害怕人工智能会取代我的工作。我更担心的或许是人们正在感受到的那种恐惧

I don't think I was ever afraid of AI taking over my job. I was more perhaps afraid of the fear that people were feeling

害怕恐惧本身。唯一需要恐惧的就是恐惧本身，伊莎贝拉说。

afraid of the fear. The only thing fear is fear itself, Isabella said.

不。是的。因为我看到身边很多人充满焦虑，我当时就想，哦，这可不太好。

No. Yes. Because I I saw that there was a lot of anxiety in folks around me, and I was like, oh, this isn't good.

她想弄清楚，这些恐惧是否有道理？伊莎贝拉是一位计算社会科学家，基本上就是她运用计算机科学技术来帮助回答社会科学问题。她与著名的麻省理工学院经济学家罗伯托·里戈邦合作。他们最终做的是将丹尼尔的O*NET研究反过来看。不是关注人工智能能帮助完成哪些任务，而是问：人类擅长什么？

She wanted to figure out, are those fears justified? Isabella is a computational social scientist, meaning basically that she incorporates computer science techniques to help answer social science y questions. She teamed up with a well known MIT economist, Roberto Rigobon. And what they ended up doing was kinda turning Daniel's O*NET research inside out. Instead of looking at what tasks AI can help do, they asked, what are humans good for?

让我们看看人类能做什么，因为我们就在这里。地球上现在有数十亿人。即使人工智能出现并自动化了所有现有工作，那我们该怎么办？对吧？这就是真正引发那个问题的原因，就像，嘿。

Let's look at what humans can do because we're here. There's billions of us in the planet right now. And even if AI came and automated all the jobs that exist, then what are we gonna do? Right? So that's what really sparked that kind of question of, like, hey.

让我们看看什么是人类能做得很好的补充性工作，而机器目前还无法做得那么好。

Let's look at what is complementary that humans can do very well that machines still can't do that well, at least for now.

为了回答这个问题，伊莎贝拉和她的合著者与很多人进行了交谈。她的合著者罗伯托·里加邦实际上已经思考这个问题多年了。他们咨询了心理学家和哲学家，最终将内容浓缩成一个单一分数。它被称为EPOC分数。这是一个缩写，每个字母代表一个他们认为人类将特别需要来补充人工智能的领域。

To answer that question, Isabella and her coauthor talked to a lot of people. Her coauthor, Roberto Rigabon, has actually been thinking about this for years. They consulted psychologists and philosophers, and they ended up condensing things down into a single score. It's called the EPOC score. It's an acronym, and each letter stands for an area where they think that humans will be especially needed to complement AI.

这有点像人性分数。E代表共情，相当人性化的特质。人工智能或许可以模拟它，但可以说，共情的全部意义在于另一个人能感受你的痛苦。P代表在场。你需要亲身在场完成任务吗？或者你的工作是否受益于面对面的协作？

It's kind of a humanness score. E stands for empathy, pretty human trait. AI can maybe simulate it, but arguably the whole point of empathy is that another human is feeling your pain. P is presence. Do you need to physically be there to do the task, or does your work benefit from face to face collaboration?

然后是O，代表观点、判断和批判性思维。但在这里，我们特别想强调人类必须做出的所有道德和伦理判断。对吧？

Then we have o for opinion, judgment, critical thinking. But here, we also really want to emphasize all the moral and ethical judgments that humans have to do. Right?

所以这有点像伦理，但你们不想再用E了。是的。C代表创造力。伊莎贝拉强调，AI是在大量现有数据上训练的。所以即使它们能写诗，在想象全新可能性方面，可以说还是不如人类。

So it's kind of like ethics, but you didn't want another e. Yes. C is for creativity. Isabella emphasizes that AI is trained on a bunch of existing data. So even if they can, like, write a poem, they're arguably not as good as humans at imagining entirely new possibilities.

然后H其实是我最喜欢的之一。H代表希望。给我讲讲这个吧。

And then H is one of my favorites actually. H is for hope. So tell me about that one.

是的，这也是我最喜欢的。因为当它出现时，我就在想，真的吗？工作中我们需要希望吗？但当你真正查看数据时，发现很多职业确实需要对未来抱有希望。

Yes. That is also my favorite. Because when it came up, I was like, really? Is hope something that we need for work? And then when you actually look at the data, there's a lot of occupations that require to have hope in the future.

这个类别的全称是希望、愿景和领导力。所以它涉及规划、设想目标并团结人们去实现。一个例子可能是药物滥用咨询师，你必须对客户的康复抱有希望。事实上，在某种程度上，这正是你被雇佣的原因。

The full name of this category is hope, vision, and leadership. So it's things that involve planning and, like, envisioning a goal and rallying people to get there. One example might be a substance abuse counselor. You gotta have hope for your client's recovery. In fact, in some ways, that is the very thing you're hired to have.

接下来，伊莎贝拉想弄清楚任何特定职业中这些不同技能的参与程度。所以她基本上用一个计算机程序来读取所有O*NET任务描述，然后为每个工作分配一个总体EPOCH分数。结果就是，莎莉，为你呈现一个列表。一个列表。一个基本上按人性化程度高低排序的工作列表。

Next, Isabella wanted to figure out how much of these various skills are involved in any given occupation. So she used essentially a computer program to read all of those O*NET tasks, and then she would assign each job an overall epoch score. The result is, Sally, for you, a list. A list. A list of jobs that essentially score higher or lower on humanness.

是的。想象一下我有多兴奋。一个列表。在列表顶部附近，例如有应急管理主任。这些人是为灾难做准备，并在灾难发生后帮助管理善后工作的。

Yes. Imagine my excitement. A list. And near the top of the list, we have, for example, emergency management director. These are people who prepare for disasters and then come in after disasters to help manage the fallout.

这项工作需要大量的判断力、同理心和临场感。事实上，各类管理人员在epoch评分上都很高。甚至像信息技术项目经理这样的职位也是如此，这让我感到惊讶。听起来这像是个计算机类的工作。

The job requires lots of judgment, lots of empathy, lots of presence. In fact, managers of all kinds scored high on epoch. Even something like information technology project managers. That was surprising to me. It kinda sounds like a computer y job.

但如果你查看他们的任务清单，会发现其中包含大量规划工作、团队领导、人员管理。总的来说，比你想象中更多的工作都涉及大量epoch要素。例如，建筑工人的同理心评分就比伊莎贝拉预期的要高。

But if you look at their list of tasks, it's a lot of planning, a lot of leading teams, managing people, and in general, more jobs than you might think have a lot of epoch going on. Construction workers, for example, scored higher than Isabella expected on empathy.

我非常惊讶。当时我在想，这是怎么回事？结果发现，在他们的职业描述中有一两项任务写着，比如要指导他人或教导经验不足的建筑工人。

I was very surprised. And I was like, what's happening here? And it turns out that there's one or two tasks in their occupational description which says they are mentoring others or teaching less experienced construction workers, for example.

在分配epoch评分时出现了一些奇怪的现象，因为有些任务对我们来说太明显了，以至于在O*NET中没有明确写出来。比如，理发师的任务清单不会写着'我必须亲自在发廊拿着剪刀'。所以很多体力劳动工作的epoch评分其实很低，尽管在没有重大机器人技术突破的情况下，这些工作实际上确实需要本人在场。

Now there were some weird things that happened in assigning epoch scores because some tasks are so obvious to us that they actually aren't explicitly written down in O*NET. Like, the task list for barber doesn't say, I have to physically be at the salon holding the scissors in my hands. So a lot of physical manual labor jobs actually scored pretty low on epoch, Even though absent some kind of, like, major robotics boom, those are jobs where you do, in fact, really have to be there.

但另一个突出点是文职工作的评分往往较低。税务申报员、保险评估员等。因此这些工作可能最容易受到人工智能的冲击。当然，所有这些都只是理论。也许人工智能会变得更像人类，或者我们根本不在乎它只是在模拟同理心。

But the other thing that sticks out is that clerical jobs tended to score low. Tax preparers, insurance appraisers. So it's possible that those jobs could be most at risk from AI. Now, of course, all of this is just a theory. Maybe AI will get a lot more human like, or maybe we just won't care that it's only simulating empathy.

但重要的是，与丹尼尔及其合著者不同，伊莎贝拉和她的合著者确实尝试根据这些人性化评分来分解不同工作的风险。

But importantly, unlike Daniel and his coauthors, Isabella and her coauthor actually did try to break down the risk for different jobs based on these humanness scores.

核心问题基本上是：人工智能是否可能突然介入并取代这个工作？或者这个工作仍然存在，但人工智能只是帮助人类？这个工作更可能被自动化还是增强化？

The question is basically, is AI likely to swoop in and steal this job? Or is the job still going to exist, but AI is just going to help humans out? Is the job likely to be automated or augmented?

伊莎贝拉的论文以一种有趣的方式探讨了这个问题。它再次使用了O*NET中的任务清单，并聚焦于一个事实：某些任务往往同时出现。所以，如果你有一堆文书任务，但同时还有一些高度依赖人际互动的关联任务，那么你的工作可能更安全。AI最终可能会增强你的能力，而不是取代你。不要把它想象成机器人抢走你的工作，而是你自己的个人仿生手臂。

Isabella's paper looks at that question in an interesting way. It takes those task lists again from O*NET, and it zeros in on the fact that some tasks tend to occur together. So if you have a bunch of clerical tasks, but also some connected tasks that are highly human, then your job might be safer. AI might end up augmenting you, not replacing you. Think of it not as a robot taking your job, but as your own personal bionic arm.

比如对教授来说，他们的一个任务可能是制作讲座幻灯片。AI大概能做到这一点。但一个关联任务——进行讲座——这非常依赖人的因素。或者以律师为例。

Like for a professor, one of their tasks might be making slides for a lecture. AI can probably do that. But a linked task, Giving the lecture. That's pretty human. Or take lawyers.

向法官进行辩论陈述的任务需要很强的临场表现力，因此很难自动化这个任务。但随后撰写相关的案情摘要，你知道，那个任务可能非常容易自动化。

The task that is delivering the argumentative of the judge requires a lot of presence, so it's really hard to automate that task. But then writing the brief about it, you know, that task might be very automatable.

你知道，这实际上让我想起了一位给我们写信的听众。他叫查理。我向伊莎贝拉提到了查理·贝克，我们那位决定推迟法学院的听众。伊莎贝拉同意丹尼尔·洛克的观点。法律领域很可能受到AI的影响。

You know, this is actually making me think of a listener who wrote into us. His name is Charlie. I told Isabella about Charlie Baker, our listener who has decided to delay law school. And Isabella agrees with Daniel Rock. The legal field is likely to be affected by AI.

更偏向文书类型的工作可以更容易地被自动化，但法律领域还有大量其他职业不会受到同样大的影响。所有需要批判性思维、判断力甚至创造力的不同职业，这些是不会消失的。

The more clerical type of jobs can be more easily automated, but there's another great number of occupation in the legal field which are not going to be as impacted. All the different occupations that require critical thinking, judgment, even creativity, that is not going to go away.

所以你在某种程度上是在告诉查理，你可以去法学院，并专注于法律中更有趣的部分。比如，努力擅长做出判断。努力擅长辩论。不要太担心文书任务

So you're kind of telling Charlie you can go to law school and think about, like, the more interesting parts of the law. Like, try to get good at judgment. Try to get good at argument. Don't worry about clerical tasks so much

因为它们可能会由机器来完成。

because they might be done by machines.

是的。完全正确。就像，学会如何思考。

Yes. Exactly. Like, learn how to think.

这和丹尼尔·洛克告诉我的有些相似。

It is kind of similar to what Daniel Rock told me.

嗯，听起来查理已经有一个非常聪明的开始了。听起来查理在考虑他作为律师的预期未来现金流的贴现率会稍高一些，因为那里的现金流风险更大。抱歉。不。但孩子们。

Well, it sounds like Charlie is already off to a very clever start. It sounds like Charlie is thinking about the discount rate on his expected future cash flows for being a lawyer as being a little bit higher, riskier cash flows there. Sorry. No. But kids.

我尤其不担心律师这个群体。他们会想办法改变游戏规则，你知道，作为一个领域，这对他们有利。对吧？

Lawyers in particular are the the group of people I'm least worried about. They will find a way to change the rules of the game that help, you know, as a as a field. Right?

他确实说过，你知道，记住那些让工作变得更有趣的律师助理，并思考你作为律师如何也能做到那样。比如，试着想象未来年轻律师可能做到哪些现在做不到的事情。

He did say, you know, remember those paralegals who made their jobs more interesting, and think about how you could do that as a lawyer. Like, try to imagine what might be possible for a young lawyer in the future that isn't possible now.

丹尼尔还为安娜·温恩——那位正在考虑转行做水管工或焊工的技术工作者——提出了一个有趣的想法。他指出，如果现在每个人都决定去做焊工，最终可能会出现焊工过剩的情况。也许工资会下降。

Daniel also had an interesting thought for Anna Winn, the tech worker who's thinking about becoming a plumber or a welder. He pointed out if everyone decides to be a welder right now, there just might end up being too many welders. Maybe wages would go down.

所以你不一定安全，但也不一定处于危险之中，无论你处于这个光谱的哪个位置。我们只是无法预知。

So you're not necessarily safe, and also you're not necessarily in danger no matter where you are along the spectrum. We just can't know.

丹尼尔和伊莎贝拉都给出了一个非常具体的建议，那就是学会使用人工智能，这样你就能准备好迎接即将到来的变化，并有望将其塑造成对自身有利的局面。这并非我最喜欢的建议，我想是因为它确实很难。掌握如何有效使用这些工具需要付出努力，更不用说如何合乎道德地使用它们了。但我的确与一个人交谈过，他让我看到了这件事如何能顺利进行。

Daniel and Isabella both had one very concrete piece of advice, which is to learn to use AI so that you can be ready to kinda roll with what's coming, hopefully shape it to your advantage. And that's not my favorite ever piece of advice. I think because it's just hard. Figuring out how to use these tools well takes work, let alone how to use them ethically. But I did talk to one person who helped me see how this could go well.

她的名字是凯特·里尔登。她是一名兽医。她告诉我，她最喜欢的动物园动物之一是南美浣熊。

Her name is Kat Reardon. She is a veterinarian. She told me that one of her favorite zoo animals is the koatis.

它们有长长的鼻子和这些令人难以置信的条纹尾巴。有一只名叫雅各布，它最喜欢的东西是烘干纸。所以，如果我把烘干纸放进口袋，它就会过来，把鼻子伸进我的口袋，然后对烘干纸兴奋不已。

They have these long noses and these and these incredible stripy tails. There was one, his name was Jacob, and his favorite thing in the world was dryer sheets. So if I, like, put dryer sheets in my pocket, he would come and, like, put his nose in my pocket and, like, get all excited about the dryer sheets.

那么，我为什么和凯特谈论这些南美浣熊和烘干纸呢？因为凯特完成了从先前不为人知的兽医到人工智能领域的职业跨越。事情是这样的：有一天，她在网上发帖说她开始使用ChatGPT来帮助她处理病历记录。做这些记录对她和其他兽医来说是一项巨大的消耗，而ChatGPT让凯特工作中这个非常烦人的部分变得快多了。

So why was I talking to Kat about this Kiwadis and dryer sheets? Because Kat has made the previously unknown veterinarian to AI career jump. Here's how it happened. She was posting online one day about how she'd started using ChatGPT to help her with her patient notes. Taking these notes is a huge drain on her and other veterinarians, and ChatGPT was making this really annoying part of Kat's job way faster.

于是她发布了这个经历，随后收到了一家AI初创公司的消息，他们说：‘实际上，我们正在尝试开发一个类似的工具卖给兽医。你想试试吗？’她试了，现在她就在那里工作，做一些事情，比如帮助AI学习它需要知道的兽医术语。她仍然从事兽医工作，并使用这个工具自动化她工作中的部分内容，比如听她的预约录音并完成笔记的初稿。

So she posted about this, and then she heard from an AI startup saying, actually, we're trying to make a tool like that to sell to vets. Do you wanna try it? She did, and now she works there doing things like helping the AI learn veterinary terms that it needs to know. She also still works as a vet, and she uses the tool to automate parts of her job, like listening to her appointments and doing a first draft of her notes.

是的。她告诉我，这以一些令人惊讶的方式提供了帮助。

Yeah. She told me it's helped in some surprising ways.

说实话，我被咬的次数会少一些，因为我的双手都放在动物身上，我能感觉到它们是否开始变得不安，能感觉到小肌肉紧张之类的，这些我以前因为担心完成记录而分心没有注意到。

Honestly, I'll I'll get bit less often because I have my hands on the animal, both hands, and I can kind of feel if they're kind of starting to get upset, and I can feel the little muscles tensing or whatever that I was distracted and not paying attention to previously because I was worried about getting my notes done.

而且因为你一只手像握着笔一样。真的。是的。是的。所以我没错。

And because you had one hand like on a pen. Literally. Yeah. Yeah. So I yeah.

它 我给了 我感觉

It I gave I feel

这和其他事情一样是个安全问题。

like it's a safety issue as much as anything else.

这正是丹尼尔和伊莎贝拉所期待的人工智能增强故事，也是我未曾想象过的。随着这些对话的进行，我不断思考这实际上正是我们都需要在此运用的特质——想象力。我原本是去寻找一份清单，一个具体的指南来帮助我应对即将到来的一切。

It's the AI augmentation story that Daniel and Isabella are hoping for, and not one that I would have imagined. And as I had these conversations, I kept thinking that that is in fact the trait we all need to be applying here. Imagination. I went in looking for a list. A concrete guide to help me navigate what's coming.

但我发现其实并没有这样的清单。现在没有，也许永远都不会有。我们即将经历的旅程会比那更加奇异。

But I learned there really is no list. Not yet, maybe not ever. We are in for a weirder ride than that.

本期节目由埃里克·梅特尔制作，玛丽·安妮·麦丘恩编辑。

Today's episode was produced by Eric Mettle and edited by Mary Anne McCune.

背景调查由塞拉·华雷斯完成，工程由罗伯特·罗德里格斯负责。亚历克斯·戈德马克是我们的执行制片人。特别感谢阿尔温德·卡鲁纳卡兰，他撰写了那篇关于律师助理使用人工智能的论文。我是萨莉·赫尔姆。

It was backtracked by Sierra Juarez and engineered by Robert Rodriguez. Alex Goldmark is our executive producer. Special thanks to Arvind Karunakaran. He wrote that paper about the paralegals using AI. I'm Sallie Helm.

我是阿曼达·阿隆舒克。这里是NPR。感谢您的收听。

And I'm Amanda Aronshuk. This is NPR. Thanks for listening.